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<li><strong>定义</strong>：超体素是点云中具有相似颜色、空间位置和法线方向的一组体素（voxel）的集合。</li>
<li><strong>类比</strong>：类似于图像中的“超像素”（Superpixel），是点云的<strong>过分割</strong>（over-segmentation）结果。</li>
<li><strong>目的</strong>：将原始点云转换为更少、更有意义的“块”，用于后续分割、识别或图分析。</li>
</ul>
<hr>
<h2 id="🔹-2-超体素-vs-体素网格下采样"><a href="#🔹-2-超体素-vs-体素网格下采样" class="headerlink" title="🔹 2. 超体素 vs 体素网格下采样"></a>🔹 2. <strong>超体素 vs 体素网格下采样</strong></h2><table>
<thead>
<tr>
<th>特性</th>
<th>体素网格滤波（Voxel Grid）</th>
<th>超体素聚类（Supervoxel Clustering）</th>
</tr>
</thead>
<tbody><tr>
<td>输出</td>
<td>下采样点云</td>
<td>一组语义一致的体素块</td>
</tr>
<tr>
<td>结构</td>
<td>简单网格</td>
<td>保持几何边界</td>
</tr>
<tr>
<td>信息保留</td>
<td>仅空间</td>
<td>空间 + 颜色 + 法线</td>
</tr>
<tr>
<td>用途</td>
<td>预处理降噪</td>
<td>高级分割、图构建</td>
</tr>
</tbody></table>
<hr>
<h2 id="🔹-3-核心参数说明"><a href="#🔹-3-核心参数说明" class="headerlink" title="🔹 3. 核心参数说明"></a>🔹 3. <strong>核心参数说明</strong></h2><table>
<thead>
<tr>
<th>参数</th>
<th>方法</th>
<th>作用</th>
<th>推荐值</th>
</tr>
</thead>
<tbody><tr>
<td><code>voxel_resolution</code></td>
<td>构造函数参数</td>
<td>体素化网格大小（体素边长）</td>
<td>0.005 ~ 0.02 m</td>
</tr>
<tr>
<td><code>seed_resolution</code></td>
<td>构造函数参数</td>
<td>决定超体素的大致尺寸</td>
<td>通常是 <code>voxel_resolution</code> 的 10~20 倍</td>
</tr>
<tr>
<td><code>setColorImportance()</code></td>
<td><code>color_importance</code></td>
<td>颜色差异的权重</td>
<td>0.0 ~ 1.0</td>
</tr>
<tr>
<td><code>setSpatialImportance()</code></td>
<td><code>spatial_importance</code></td>
<td>空间距离的权重</td>
<td>0.0 ~ 1.0</td>
</tr>
<tr>
<td><code>setNormalImportance()</code></td>
<td><code>normal_importance</code></td>
<td>法线方向差异的权重</td>
<td>通常设为 1.0（最重要）</td>
</tr>
<tr>
<td><code>setUseSingleCameraTransform()</code></td>
<td><code>false</code></td>
<td>是否假设点云来自单个相机视角</td>
<td>多视角数据建议设为 <code>false</code></td>
</tr>
</tbody></table>
<blockquote>
<p>✅ <strong>权重建议</strong>：<code>normal &gt; spatial &gt; color</code>，例如 <code>(1.0, 0.4, 0.2)</code></p>
</blockquote>
<hr>
<h2 id="🔹-4-输出结果详解"><a href="#🔹-4-输出结果详解" class="headerlink" title="🔹 4. 输出结果详解"></a>🔹 4. <strong>输出结果详解</strong></h2><table>
<thead>
<tr>
<th>方法</th>
<th>返回类型</th>
<th>说明</th>
</tr>
</thead>
<tbody><tr>
<td><code>getVoxelCentroidCloud()</code></td>
<td><code>PointCloudT::Ptr</code></td>
<td>所有体素的中心点（下采样点云）</td>
</tr>
<tr>
<td><code>getLabeledVoxelCloud()</code></td>
<td><code>PointLCloudT::Ptr</code></td>
<td>每个体素带有一个 <code>label</code> 字段，可用于着色</td>
</tr>
<tr>
<td><code>makeSupervoxelNormalCloud()</code></td>
<td><code>PointNCloudT::Ptr</code></td>
<td>每个超体素的法线（中心点 + 法向量）</td>
</tr>
<tr>
<td><code>getSupervoxelAdjacency()</code></td>
<td><code>multimap&lt;uint32_t, uint32_t&gt;</code></td>
<td>超体素之间的邻接关系图</td>
</tr>
</tbody></table>
<hr>
<h2 id="🔹-5-邻接图（Adjacency-Graph）构建"><a href="#🔹-5-邻接图（Adjacency-Graph）构建" class="headerlink" title="🔹 5. 邻接图（Adjacency Graph）构建"></a>🔹 5. <strong>邻接图（Adjacency Graph）构建</strong></h2><ul>
<li>使用 <code>std::multimap&lt;uint32_t, uint32_t&gt;</code> 存储邻接关系。</li>
<li>键（key）是当前超体素标签，值（value）是其邻居标签。</li>
<li>使用 <code>equal_range(label)</code> 获取所有邻居。</li>
<li>使用 <code>upper_bound(label)</code> 跳过重复键，遍历下一个标签。</li>
</ul>
<hr>
<h2 id="🔹-6-可视化技巧"><a href="#🔹-6-可视化技巧" class="headerlink" title="🔹 6. 可视化技巧"></a>🔹 6. <strong>可视化技巧</strong></h2><ul>
<li>✅ <code>addPointCloud()</code> + <code>PointLT</code>：自动根据 <code>label</code> 字段着色，显示超体素分割结果。</li>
<li>✅ <code>addPointCloudNormals()</code>：可视化超体素法线方向。</li>
<li>✅ <code>addLine()</code>：绘制超体素之间的连接线，形成图结构。</li>
<li>✅ <code>addSphere()</code>：突出显示超体素中心。</li>
<li>✅ <code>setShapeRenderingProperties()</code>：控制线宽、颜色、透明度、着色模式。</li>
</ul>
<hr>
<h2 id="🔹-7-典型应用场景"><a href="#🔹-7-典型应用场景" class="headerlink" title="🔹 7. 典型应用场景"></a>🔹 7. <strong>典型应用场景</strong></h2><ul>
<li>✅ <strong>点云分割预处理</strong>：将点云转为超体素块，再进行合并或分类。</li>
<li>✅ <strong>物体识别</strong>：提取超体素特征（如法线、曲率）进行匹配。</li>
<li>✅ <strong>场景理解</strong>：构建超体素图，用于图神经网络（GNN）输入。</li>
<li>✅ <strong>机器人抓取</strong>：识别可抓取的平面或物体。</li>
</ul>
<hr>
<h2 id="🔹-8-编译配置（CMakeLists-txt）"><a href="#🔹-8-编译配置（CMakeLists-txt）" class="headerlink" title="🔹 8. 编译配置（CMakeLists.txt）"></a>🔹 8. <strong>编译配置（CMakeLists.txt）</strong></h2><figure class="highlight cmake"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">cmake_minimum_required</span>(VERSION <span class="number">3.10</span>)</span><br><span class="line"><span class="keyword">project</span>(supervoxel_clustering)</span><br><span class="line"></span><br><span class="line"><span class="keyword">find_package</span>(PCL REQUIRED COMPONENTS </span><br><span class="line">    common </span><br><span class="line">    io </span><br><span class="line">    filters </span><br><span class="line">    features </span><br><span class="line">    segmentation </span><br><span class="line">    visualization</span><br><span class="line">)</span><br><span class="line"></span><br><span class="line"><span class="keyword">add_executable</span>(supervoxel_clustering supervoxel_clustering.cpp)</span><br><span class="line"></span><br><span class="line"><span class="keyword">include_directories</span>(<span class="variable">$&#123;PCL_INCLUDE_DIRS&#125;</span>)</span><br><span class="line"><span class="keyword">link_directories</span>(<span class="variable">$&#123;PCL_LIBRARY_DIRS&#125;</span>)</span><br><span class="line"><span class="keyword">add_definitions</span>(<span class="variable">$&#123;PCL_DEFINITIONS&#125;</span>)</span><br><span class="line"></span><br><span class="line"><span class="keyword">target_link_libraries</span>(supervoxel_clustering <span class="variable">$&#123;PCL_LIBRARIES&#125;</span>)</span><br></pre></td></tr></table></figure>

<hr>
<h2 id="🔹-9-命令行使用方式"><a href="#🔹-9-命令行使用方式" class="headerlink" title="🔹 9. 命令行使用方式"></a>🔹 9. <strong>命令行使用方式</strong></h2><figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">./supervoxel_clustering input.pcd -v 0.01 -s 0.05 -c 0.1 -z 0.3 -n 1.0 --NT</span><br></pre></td></tr></table></figure>

<table>
<thead>
<tr>
<th>参数</th>
<th>说明</th>
</tr>
</thead>
<tbody><tr>
<td><code>-v 0.01</code></td>
<td>体素分辨率 1cm</td>
</tr>
<tr>
<td><code>-s 0.05</code></td>
<td>种子分辨率 5cm</td>
</tr>
<tr>
<td><code>-c 0.1</code></td>
<td>颜色权重低</td>
</tr>
<tr>
<td><code>-z 0.3</code></td>
<td>空间权重中等</td>
</tr>
<tr>
<td><code>-n 1.0</code></td>
<td>法线权重高</td>
</tr>
<tr>
<td><code>--NT</code></td>
<td>禁用单相机变换</td>
</tr>
</tbody></table>
<hr>
<h2 id="✅-三、总结"><a href="#✅-三、总结" class="headerlink" title="✅ 三、总结"></a>✅ 三、总结</h2><blockquote>
<p><strong>PCL 的 <code>SupervoxelClustering</code> 是一种基于体素的过分割算法，通过融合空间、颜色和法线信息，将点云划分为语义一致的“超体素”块。它不仅可用于降维和去噪，更能为后续的高级处理（如图分割、物体识别）提供结构化输入。</strong></p>
</blockquote>
<p>📌 <strong>优点</strong>：</p>
<ul>
<li>保留几何边界</li>
<li>融合多模态信息</li>
<li>输出结构化图</li>
</ul>
<p>📌 <strong>局限</strong>：</p>
<ul>
<li>对参数敏感</li>
<li>计算开销较大</li>
<li>需要彩色点云效果更佳</li>
</ul>
<p>📌 <strong>建议</strong>：先使用默认参数测试，再逐步调整 <code>seed_resolution</code> 和权重。</p>
<hr>
<h2 id="代码实现"><a href="#代码实现" class="headerlink" title="代码实现"></a>代码实现</h2><figure class="highlight cpp"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span 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class="line">59</span><br><span class="line">60</span><br><span class="line">61</span><br><span class="line">62</span><br><span class="line">63</span><br><span class="line">64</span><br><span class="line">65</span><br><span class="line">66</span><br><span class="line">67</span><br><span class="line">68</span><br><span class="line">69</span><br><span class="line">70</span><br><span class="line">71</span><br><span class="line">72</span><br><span class="line">73</span><br><span class="line">74</span><br><span class="line">75</span><br><span class="line">76</span><br><span class="line">77</span><br><span class="line">78</span><br><span class="line">79</span><br><span class="line">80</span><br><span class="line">81</span><br><span class="line">82</span><br><span class="line">83</span><br><span class="line">84</span><br><span class="line">85</span><br><span class="line">86</span><br><span class="line">87</span><br><span class="line">88</span><br><span class="line">89</span><br><span 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class="line">180</span><br><span class="line">181</span><br><span class="line">182</span><br><span class="line">183</span><br><span class="line">184</span><br><span class="line">185</span><br><span class="line">186</span><br><span class="line">187</span><br><span class="line">188</span><br><span class="line">189</span><br><span class="line">190</span><br><span class="line">191</span><br><span class="line">192</span><br><span class="line">193</span><br><span class="line">194</span><br><span class="line">195</span><br><span class="line">196</span><br><span class="line">197</span><br><span class="line">198</span><br><span class="line">199</span><br><span class="line">200</span><br><span class="line">201</span><br><span class="line">202</span><br><span class="line">203</span><br><span class="line">204</span><br></pre></td><td class="code"><pre><span class="line"><span class="meta">#<span class="keyword">include</span> <span class="string">&lt;pcl/console/parse.h&gt;</span>               <span class="comment">// PCL 命令行参数解析</span></span></span><br><span class="line"><span class="meta">#<span class="keyword">include</span> <span class="string">&lt;pcl/point_cloud.h&gt;</span>                 <span class="comment">// 点云基础类</span></span></span><br><span class="line"><span class="meta">#<span class="keyword">include</span> <span class="string">&lt;pcl/point_types.h&gt;</span>                 <span class="comment">// 内置点类型（如PointXYZRGBA）</span></span></span><br><span class="line"><span class="meta">#<span class="keyword">include</span> <span class="string">&lt;pcl/io/pcd_io.h&gt;</span>                   <span class="comment">// PCD 文件读写</span></span></span><br><span class="line"><span class="meta">#<span class="keyword">include</span> <span class="string">&lt;pcl/visualization/pcl_visualizer.h&gt;</span><span class="comment">// 可视化工具</span></span></span><br><span class="line"><span class="meta">#<span class="keyword">include</span> <span class="string">&lt;pcl/segmentation/supervoxel_clustering.h&gt;</span> <span class="comment">// 超体素聚类头文件</span></span></span><br><span class="line"></span><br><span class="line"><span class="comment">// 定义常用类型别名，简化代码</span></span><br><span class="line"><span class="keyword">typedef</span> pcl::PointXYZRGBA PointT;             <span class="comment">// 使用带颜色的XYZ点</span></span><br><span class="line"><span class="keyword">typedef</span> pcl::PointCloud&lt;PointT&gt; PointCloudT;  <span class="comment">// 点云类型</span></span><br><span class="line"><span class="keyword">typedef</span> pcl::PointNormal PointNT;             <span class="comment">// 法线点类型</span></span><br><span class="line"><span class="keyword">typedef</span> pcl::PointCloud&lt;PointNT&gt; PointNCloudT;<span class="comment">// 法线点云</span></span><br><span class="line"><span class="keyword">typedef</span> pcl::PointXYZL PointLT;               <span class="comment">// 带标签的点（用于超体素标记）</span></span><br><span class="line"><span class="keyword">typedef</span> pcl::PointCloud&lt;PointLT&gt; PointLCloudT;<span class="comment">// 标记点云</span></span><br><span class="line"></span><br><span class="line"><span class="comment">// 函数声明：用于在可视化器中添加超体素连接线和球体</span></span><br><span class="line"><span class="function"><span class="type">void</span> <span class="title">addSupervoxelConnectionsToViewer</span> <span class="params">(PointT &amp;supervoxel_center,</span></span></span><br><span class="line"><span class="params"><span class="function">                                       PointCloudT &amp;adjacent_supervoxel_centers,</span></span></span><br><span class="line"><span class="params"><span class="function">                                       std::string supervoxel_name,</span></span></span><br><span class="line"><span class="params"><span class="function">                                       boost::shared_ptr&lt;pcl::visualization::PCLVisualizer&gt; &amp; viewer)</span></span>;</span><br><span class="line"></span><br><span class="line"><span class="function"><span class="type">int</span> <span class="title">main</span> <span class="params">(<span class="type">int</span> argc, <span class="type">char</span> ** argv)</span></span></span><br><span class="line"><span class="function"></span>&#123;</span><br><span class="line">  <span class="comment">// 检查是否提供了输入文件</span></span><br><span class="line">  <span class="keyword">if</span> (argc &lt; <span class="number">2</span>)</span><br><span class="line">  &#123;</span><br><span class="line">    pcl::console::<span class="built_in">print_error</span> (<span class="string">&quot;Syntax is: %s &lt;pcd-file&gt; \n &quot;</span></span><br><span class="line">                               <span class="string">&quot;--NT Disables the single cloud transform \n&quot;</span></span><br><span class="line">                               <span class="string">&quot;-v &lt;voxel resolution&gt;\n-s &lt;seed resolution&gt;\n&quot;</span></span><br><span class="line">                               <span class="string">&quot;-c &lt;color weight&gt; \n-z &lt;spatial weight&gt; \n&quot;</span></span><br><span class="line">                               <span class="string">&quot;-n &lt;normal_weight&gt;\n&quot;</span>, argv[<span class="number">0</span>]);</span><br><span class="line">    <span class="keyword">return</span> (<span class="number">1</span>); <span class="comment">// 参数不足则报错退出</span></span><br><span class="line">  &#125;</span><br><span class="line"></span><br><span class="line">  <span class="comment">// 创建指向输入点云的共享指针</span></span><br><span class="line">  PointCloudT::Ptr cloud = boost::<span class="built_in">make_shared</span>&lt;PointCloudT&gt; ();</span><br><span class="line">  pcl::console::<span class="built_in">print_highlight</span> (<span class="string">&quot;Loading point cloud...\n&quot;</span>); <span class="comment">// 高亮提示加载中</span></span><br><span class="line"></span><br><span class="line">  <span class="comment">// 加载PCD文件到点云对象</span></span><br><span class="line">  <span class="keyword">if</span> (pcl::io::<span class="built_in">loadPCDFile</span>&lt;PointT&gt; (argv[<span class="number">1</span>], *cloud))</span><br><span class="line">  &#123;</span><br><span class="line">    pcl::console::<span class="built_in">print_error</span> (<span class="string">&quot;Error loading cloud file!\n&quot;</span>); <span class="comment">// 加载失败</span></span><br><span class="line">    <span class="keyword">return</span> (<span class="number">1</span>);</span><br><span class="line">  &#125;</span><br><span class="line">  std::cout &lt;&lt; <span class="string">&quot;point size of input: &quot;</span> &lt;&lt; cloud-&gt;<span class="built_in">size</span>() &lt;&lt; std::endl; <span class="comment">// 输出点数量</span></span><br><span class="line"></span><br><span class="line">  <span class="comment">// 检查是否禁用单相机变换（默认启用）</span></span><br><span class="line">  <span class="type">bool</span> disable_transform = pcl::console::<span class="built_in">find_switch</span> (argc, argv, <span class="string">&quot;--NT&quot;</span>);</span><br><span class="line"></span><br><span class="line">  <span class="comment">// 设置体素分辨率（体素化网格大小），默认0.008m (8mm)</span></span><br><span class="line">  <span class="type">float</span> voxel_resolution = <span class="number">0.008f</span>;</span><br><span class="line">  <span class="type">bool</span> voxel_res_specified = pcl::console::<span class="built_in">find_switch</span> (argc, argv, <span class="string">&quot;-v&quot;</span>); <span class="comment">// 是否指定</span></span><br><span class="line">  <span class="keyword">if</span> (voxel_res_specified)</span><br><span class="line">    pcl::console::<span class="built_in">parse</span> (argc, argv, <span class="string">&quot;-v&quot;</span>, voxel_resolution); <span class="comment">// 解析用户输入值</span></span><br><span class="line"></span><br><span class="line">  <span class="comment">// 设置种子分辨率（决定超体素的大致大小），默认0.1m (10cm)</span></span><br><span class="line">  <span class="type">float</span> seed_resolution = <span class="number">0.1f</span>;</span><br><span class="line">  <span class="type">bool</span> seed_res_specified = pcl::console::<span class="built_in">find_switch</span> (argc, argv, <span class="string">&quot;-s&quot;</span>);</span><br><span class="line">  <span class="keyword">if</span> (seed_res_specified)</span><br><span class="line">    pcl::console::<span class="built_in">parse</span> (argc, argv, <span class="string">&quot;-s&quot;</span>, seed_resolution);</span><br><span class="line"></span><br><span class="line">  <span class="comment">// 设置颜色权重，默认0.2（颜色差异的影响）</span></span><br><span class="line">  <span class="type">float</span> color_importance = <span class="number">0.2f</span>;</span><br><span class="line">  <span class="keyword">if</span> (pcl::console::<span class="built_in">find_switch</span> (argc, argv, <span class="string">&quot;-c&quot;</span>))</span><br><span class="line">    pcl::console::<span class="built_in">parse</span> (argc, argv, <span class="string">&quot;-c&quot;</span>, color_importance);</span><br><span class="line"></span><br><span class="line">  <span class="comment">// 设置空间权重，默认0.4（空间距离的影响）</span></span><br><span class="line">  <span class="type">float</span> spatial_importance = <span class="number">0.4f</span>;</span><br><span class="line">  <span class="keyword">if</span> (pcl::console::<span class="built_in">find_switch</span> (argc, argv, <span class="string">&quot;-z&quot;</span>))</span><br><span class="line">    pcl::console::<span class="built_in">parse</span> (argc, argv, <span class="string">&quot;-z&quot;</span>, spatial_importance);</span><br><span class="line"></span><br><span class="line">  <span class="comment">// 设置法线权重，默认1.0（法线方向差异的影响）</span></span><br><span class="line">  <span class="type">float</span> normal_importance = <span class="number">1.0f</span>;</span><br><span class="line">  <span class="keyword">if</span> (pcl::console::<span class="built_in">find_switch</span> (argc, argv, <span class="string">&quot;-n&quot;</span>))</span><br><span class="line">    pcl::console::<span class="built_in">parse</span> (argc, argv, <span class="string">&quot;-n&quot;</span>, normal_importance);</span><br><span class="line"></span><br><span class="line">  <span class="comment">//////////////////////////////</span></span><br><span class="line">  <span class="comment">////// This is how to use supervoxels</span></span><br><span class="line">  <span class="comment">//////////////////////////////</span></span><br><span class="line"></span><br><span class="line">  <span class="comment">// 创建超体素聚类对象，传入体素和种子分辨率</span></span><br><span class="line">  <span class="function">pcl::SupervoxelClustering&lt;PointT&gt; <span class="title">super</span> <span class="params">(voxel_resolution, seed_resolution)</span></span>;</span><br><span class="line"></span><br><span class="line">  <span class="comment">// 如果用户指定 --NT，则禁用单相机变换（适用于非深度相机数据）</span></span><br><span class="line">  <span class="keyword">if</span> (disable_transform)</span><br><span class="line">    super.<span class="built_in">setUseSingleCameraTransform</span> (<span class="literal">false</span>);</span><br><span class="line"></span><br><span class="line">  super.<span class="built_in">setInputCloud</span> (cloud);                     <span class="comment">// 设置输入点云</span></span><br><span class="line">  super.<span class="built_in">setColorImportance</span> (color_importance);     <span class="comment">// 设置颜色权重</span></span><br><span class="line">  super.<span class="built_in">setSpatialImportance</span> (spatial_importance); <span class="comment">// 设置空间权重</span></span><br><span class="line">  super.<span class="built_in">setNormalImportance</span> (normal_importance);   <span class="comment">// 设置法线权重</span></span><br><span class="line"></span><br><span class="line">  <span class="comment">// 存储所有超体素的映射：label -&gt; Supervoxel&lt;PointT&gt;::Ptr</span></span><br><span class="line">  std::map&lt;<span class="type">uint32_t</span>, pcl::Supervoxel&lt;PointT&gt;::Ptr&gt; supervoxel_clusters;</span><br><span class="line"></span><br><span class="line">  pcl::console::<span class="built_in">print_highlight</span> (<span class="string">&quot;Extracting supervoxels!\n&quot;</span>);</span><br><span class="line">  super.<span class="built_in">extract</span> (supervoxel_clusters); <span class="comment">// 执行超体素提取</span></span><br><span class="line">  pcl::console::<span class="built_in">print_info</span> (<span class="string">&quot;Found %d supervoxels\n&quot;</span>, supervoxel_clusters.<span class="built_in">size</span> ()); <span class="comment">// 输出数量</span></span><br><span class="line"></span><br><span class="line">  <span class="comment">// 创建可视化窗口</span></span><br><span class="line">  <span class="function">boost::shared_ptr&lt;pcl::visualization::PCLVisualizer&gt; <span class="title">viewer</span> <span class="params">(<span class="keyword">new</span> pcl::visualization::PCLVisualizer (<span class="string">&quot;supervoxel_clustering&quot;</span>))</span></span>;</span><br><span class="line">  viewer-&gt;<span class="built_in">setBackgroundColor</span> (<span class="number">1</span>, <span class="number">1</span>, <span class="number">1</span>); <span class="comment">// 白色背景</span></span><br><span class="line"></span><br><span class="line">  <span class="comment">// 获取体素中心点云（即下采样后的点云）</span></span><br><span class="line">  PointCloudT::Ptr voxel_centroid_cloud = super.<span class="built_in">getVoxelCentroidCloud</span> ();</span><br><span class="line">  std::cout &lt;&lt; <span class="string">&quot;voxel centroids: &quot;</span> &lt;&lt; voxel_centroid_cloud-&gt;<span class="built_in">size</span>() &lt;&lt; std::endl;</span><br><span class="line"></span><br><span class="line">  <span class="keyword">if</span> (<span class="number">0</span>) <span class="comment">// 可视化并保存体素中心（可选）</span></span><br><span class="line">  &#123;</span><br><span class="line">    viewer-&gt;<span class="built_in">addPointCloud</span>&lt;PointT&gt;(voxel_centroid_cloud, <span class="string">&quot;voxel centroids&quot;</span>);</span><br><span class="line">    pcl::io::<span class="built_in">savePCDFile</span>(<span class="string">&quot;voxel_centroids.pcd&quot;</span>, *voxel_centroid_cloud);</span><br><span class="line">    viewer-&gt;<span class="built_in">setPointCloudRenderingProperties</span> (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, <span class="number">4</span>, <span class="string">&quot;voxel centroids&quot;</span>);</span><br><span class="line">    viewer-&gt;<span class="built_in">setPointCloudRenderingProperties</span> (pcl::visualization::PCL_VISUALIZER_OPACITY, <span class="number">0.5</span>, <span class="string">&quot;voxel centroids&quot;</span>);</span><br><span class="line">  &#125;</span><br><span class="line"></span><br><span class="line">  <span class="comment">// 获取标记后的体素点云（每个点有一个 label 字段）</span></span><br><span class="line">  PointLCloudT::Ptr labeled_voxel_cloud = super.<span class="built_in">getLabeledVoxelCloud</span> ();</span><br><span class="line"></span><br><span class="line">  <span class="keyword">if</span> (<span class="number">1</span>) <span class="comment">// 可视化并保存标记点云（推荐开启）</span></span><br><span class="line">  &#123;</span><br><span class="line">    pcl::io::<span class="built_in">savePCDFile</span>(<span class="string">&quot;labeled_voxels.pcd&quot;</span>, *labeled_voxel_cloud);</span><br><span class="line">    viewer-&gt;<span class="built_in">addPointCloud</span> (labeled_voxel_cloud, <span class="string">&quot;labeled voxels&quot;</span>);</span><br><span class="line">    std::cout &lt;&lt; <span class="string">&quot;labeled voxels: &quot;</span> &lt;&lt; labeled_voxel_cloud-&gt;<span class="built_in">size</span>() &lt;&lt; std::endl;</span><br><span class="line">    viewer-&gt;<span class="built_in">setPointCloudRenderingProperties</span> (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, <span class="number">3</span>, <span class="string">&quot;labeled voxels&quot;</span>);</span><br><span class="line">    <span class="comment">// viewer-&gt;setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_OPACITY, 0.8, &quot;labeled voxels&quot;);</span></span><br><span class="line">  &#125;</span><br><span class="line"></span><br><span class="line">  <span class="comment">// 生成每个超体素的法线点云</span></span><br><span class="line">  PointNCloudT::Ptr sv_normal_cloud = super.<span class="built_in">makeSupervoxelNormalCloud</span> (supervoxel_clusters);</span><br><span class="line"></span><br><span class="line">  <span class="keyword">if</span> (<span class="number">0</span>) <span class="comment">// 可视化超体素法线（可选）</span></span><br><span class="line">    viewer-&gt;<span class="built_in">addPointCloudNormals</span>&lt;pcl::PointNormal&gt; (sv_normal_cloud, <span class="number">1</span>, <span class="number">0.05f</span>, <span class="string">&quot;supervoxel_normals&quot;</span>);</span><br><span class="line"></span><br><span class="line">  pcl::console::<span class="built_in">print_highlight</span> (<span class="string">&quot;Getting supervoxel adjacency\n&quot;</span>);</span><br><span class="line">  <span class="comment">// 存储超体素之间的邻接关系：label1 -&gt; label2</span></span><br><span class="line">  std::multimap&lt;<span class="type">uint32_t</span>, <span class="type">uint32_t</span>&gt; supervoxel_adjacency;</span><br><span class="line">  super.<span class="built_in">getSupervoxelAdjacency</span> (supervoxel_adjacency); <span class="comment">// 获取邻接图</span></span><br><span class="line">  std::cout &lt;&lt; <span class="string">&quot;size of supervoxel_adjacency: &quot;</span> &lt;&lt; supervoxel_adjacency.<span class="built_in">size</span>() &lt;&lt; std::endl;</span><br><span class="line"></span><br><span class="line">  <span class="comment">// 遍历邻接图，为每个超体素添加连接线</span></span><br><span class="line">  std::multimap&lt;<span class="type">uint32_t</span>, <span class="type">uint32_t</span>&gt;::iterator label_itr = supervoxel_adjacency.<span class="built_in">begin</span> ();</span><br><span class="line">  <span class="keyword">for</span> (; label_itr != supervoxel_adjacency.<span class="built_in">end</span> (); )</span><br><span class="line">  &#123;</span><br><span class="line">    <span class="type">uint32_t</span> supervoxel_label = label_itr-&gt;first; <span class="comment">// 当前超体素标签</span></span><br><span class="line">    pcl::Supervoxel&lt;PointT&gt;::Ptr supervoxel = supervoxel_clusters.<span class="built_in">at</span> (supervoxel_label); <span class="comment">// 获取该超体素</span></span><br><span class="line"></span><br><span class="line">    <span class="comment">// 构造相邻超体素中心点云</span></span><br><span class="line">    PointCloudT adjacent_supervoxel_centers;</span><br><span class="line">    std::multimap&lt;<span class="type">uint32_t</span>, <span class="type">uint32_t</span>&gt;::iterator adjacent_itr = supervoxel_adjacency.<span class="built_in">equal_range</span> (supervoxel_label).first;</span><br><span class="line">    <span class="keyword">for</span> (; adjacent_itr != supervoxel_adjacency.<span class="built_in">equal_range</span> (supervoxel_label).second; ++adjacent_itr)</span><br><span class="line">    &#123;</span><br><span class="line">      pcl::Supervoxel&lt;PointT&gt;::Ptr neighbor_supervoxel = supervoxel_clusters.<span class="built_in">at</span> (adjacent_itr-&gt;second);</span><br><span class="line">      adjacent_supervoxel_centers.<span class="built_in">push_back</span> (neighbor_supervoxel-&gt;centroid_); <span class="comment">// 添加邻居中心</span></span><br><span class="line">    &#125;</span><br><span class="line"></span><br><span class="line">    <span class="comment">// 生成唯一名称</span></span><br><span class="line">    std::stringstream ss;</span><br><span class="line">    ss &lt;&lt; <span class="string">&quot;supervoxel_&quot;</span> &lt;&lt; supervoxel_label;</span><br><span class="line"></span><br><span class="line">    <span class="comment">// 调用函数绘制从当前超体素中心到所有邻居的连接线</span></span><br><span class="line">    <span class="built_in">addSupervoxelConnectionsToViewer</span> (supervoxel-&gt;centroid_, adjacent_supervoxel_centers, ss.<span class="built_in">str</span> (), viewer);</span><br><span class="line"></span><br><span class="line">    <span class="comment">// 跳过所有相同键值的条目，进入下一个标签</span></span><br><span class="line">    label_itr = supervoxel_adjacency.<span class="built_in">upper_bound</span> (supervoxel_label);</span><br><span class="line">  &#125;</span><br><span class="line"></span><br><span class="line">  <span class="comment">// 主循环：持续刷新可视化窗口直到关闭</span></span><br><span class="line">  <span class="keyword">while</span> (!viewer-&gt;<span class="built_in">wasStopped</span> ())</span><br><span class="line">  &#123;</span><br><span class="line">    viewer-&gt;<span class="built_in">spinOnce</span>();</span><br><span class="line">  &#125;</span><br><span class="line"></span><br><span class="line">  <span class="keyword">return</span> (<span class="number">0</span>);</span><br><span class="line">&#125;</span><br><span class="line"></span><br><span class="line"><span class="comment">// 自定义函数：在可视化器中为一个超体素绘制到其邻居的连接线和中心球体</span></span><br><span class="line"><span class="function"><span class="type">void</span> <span class="title">addSupervoxelConnectionsToViewer</span> <span class="params">(PointT &amp;supervoxel_center,</span></span></span><br><span class="line"><span class="params"><span class="function">                                       PointCloudT &amp;adjacent_supervoxel_centers,</span></span></span><br><span class="line"><span class="params"><span class="function">                                       std::string supervoxel_name,</span></span></span><br><span class="line"><span class="params"><span class="function">                                       boost::shared_ptr&lt;pcl::visualization::PCLVisualizer&gt; &amp; viewer)</span></span></span><br><span class="line"><span class="function"></span>&#123;</span><br><span class="line">  <span class="type">int</span> i = <span class="number">0</span>;</span><br><span class="line">  PointCloudT::iterator adjacent_itr = adjacent_supervoxel_centers.<span class="built_in">begin</span> ();</span><br><span class="line">  <span class="keyword">for</span> (; adjacent_itr != adjacent_supervoxel_centers.<span class="built_in">end</span> (); ++adjacent_itr)</span><br><span class="line">  &#123;</span><br><span class="line">    std::stringstream ss;</span><br><span class="line">    ss &lt;&lt; supervoxel_name &lt;&lt; i; <span class="comment">// 生成唯一ID</span></span><br><span class="line"></span><br><span class="line">    <span class="comment">// 添加连接线：从中心到邻居</span></span><br><span class="line">    viewer-&gt;<span class="built_in">addLine</span>(supervoxel_center, *adjacent_itr, ss.<span class="built_in">str</span>());</span><br><span class="line"></span><br><span class="line">    <span class="comment">// 设置线的样式：宽度、颜色（绿色）</span></span><br><span class="line">    viewer-&gt;<span class="built_in">setShapeRenderingProperties</span>(pcl::visualization::PCL_VISUALIZER_LINE_WIDTH, <span class="number">3</span>, ss.<span class="built_in">str</span>());</span><br><span class="line">    viewer-&gt;<span class="built_in">setShapeRenderingProperties</span>(pcl::visualization::PCL_VISUALIZER_COLOR, <span class="number">0</span>, <span class="number">255</span>, <span class="number">0</span>, ss.<span class="built_in">str</span>());</span><br><span class="line"></span><br><span class="line">    <span class="comment">// 添加中心球体（蓝色）</span></span><br><span class="line">    ss &lt;&lt; supervoxel_name &lt;&lt; i; <span class="comment">// 注意：这里重复使用了ss，应改为新stringstream</span></span><br><span class="line">    viewer-&gt;<span class="built_in">addSphere</span>(supervoxel_center, <span class="number">0.008</span>, <span class="number">0</span>, <span class="number">0</span>, <span class="number">255</span>, ss.<span class="built_in">str</span>());</span><br><span class="line">    viewer-&gt;<span class="built_in">setShapeRenderingProperties</span>(pcl::visualization::PCL_VISUALIZER_SHADING,</span><br><span class="line">                                        pcl::visualization::PCL_VISUALIZER_SHADING_GOURAUD, ss.<span class="built_in">str</span>());</span><br><span class="line">    <span class="comment">// viewer-&gt;setShapeRenderingProperties(pcl::visualization::PCL_VISUALIZER_OPACITY,0.9,ss.str());</span></span><br><span class="line">    i++;</span><br><span class="line">  &#125;</span><br><span class="line">&#125;</span><br></pre></td></tr></table></figure>

<blockquote>
<p>⚠️ <strong>注意</strong>：<code>addSupervoxelConnectionsToViewer</code> 函数中 <code>ss</code> 被重复使用，可能导致ID冲突。建议修改为：</p>
<figure class="highlight cpp"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br></pre></td><td class="code"><pre><span class="line">std::stringstream line_id, sphere_id;</span><br><span class="line">line_id &lt;&lt; supervoxel_name &lt;&lt; <span class="string">&quot;_line_&quot;</span> &lt;&lt; i;</span><br><span class="line">sphere_id &lt;&lt; supervoxel_name &lt;&lt; <span class="string">&quot;_sphere_&quot;</span> &lt;&lt; i;</span><br><span class="line">viewer-&gt;<span class="built_in">addLine</span>(..., line_id.<span class="built_in">str</span>());</span><br><span class="line">viewer-&gt;<span class="built_in">addSphere</span>(..., sphere_id.<span class="built_in">str</span>());</span><br></pre></td></tr></table></figure></blockquote>
<hr>
<p><img src="https://ckyfi9zero.github.io/picx-images-hosting/20250805/image.1lc4xozbod.png" alt="image"></p>
</article><div class="post-copyright"><div class="post-copyright__author"><span class="post-copyright-meta"><i class="fas fa-circle-user fa-fw"></i>文章作者: </span><span class="post-copyright-info"><a href="https://ckyfi9zero.github.io">Fi9zero</a></span></div><div class="post-copyright__type"><span class="post-copyright-meta"><i class="fas fa-square-arrow-up-right fa-fw"></i>文章链接: </span><span class="post-copyright-info"><a href="https://ckyfi9zero.github.io/2025/08/05/2025-08-05-%E5%9F%BA%E4%BA%8E%E8%B6%85%E4%BD%93%E7%B4%A0%E7%9A%84%E7%82%B9%E4%BA%91%E5%88%86%E5%89%B2/">https://ckyfi9zero.github.io/2025/08/05/2025-08-05-%E5%9F%BA%E4%BA%8E%E8%B6%85%E4%BD%93%E7%B4%A0%E7%9A%84%E7%82%B9%E4%BA%91%E5%88%86%E5%89%B2/</a></span></div><div class="post-copyright__notice"><span class="post-copyright-meta"><i class="fas fa-circle-exclamation fa-fw"></i>版权声明: </span><span class="post-copyright-info">本博客所有文章除特别声明外，均采用 <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/" target="_blank">CC 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class="toc-link" href="#%E8%B6%85%E4%BD%93%E7%B4%A0%E5%88%86%E5%89%B2"><span class="toc-number">1.</span> <span class="toc-text">超体素分割</span></a><ol class="toc-child"><li class="toc-item toc-level-2"><a class="toc-link" href="#%F0%9F%94%B9-1-%E4%BB%80%E4%B9%88%E6%98%AF%E8%B6%85%E4%BD%93%E7%B4%A0%EF%BC%88Supervoxel%EF%BC%89%EF%BC%9F"><span class="toc-number">1.1.</span> <span class="toc-text">🔹 1. 什么是超体素（Supervoxel）？</span></a></li><li class="toc-item toc-level-2"><a class="toc-link" href="#%F0%9F%94%B9-2-%E8%B6%85%E4%BD%93%E7%B4%A0-vs-%E4%BD%93%E7%B4%A0%E7%BD%91%E6%A0%BC%E4%B8%8B%E9%87%87%E6%A0%B7"><span class="toc-number">1.2.</span> <span class="toc-text">🔹 2. 超体素 vs 体素网格下采样</span></a></li><li class="toc-item toc-level-2"><a class="toc-link" href="#%F0%9F%94%B9-3-%E6%A0%B8%E5%BF%83%E5%8F%82%E6%95%B0%E8%AF%B4%E6%98%8E"><span class="toc-number">1.3.</span> <span class="toc-text">🔹 3. 核心参数说明</span></a></li><li class="toc-item toc-level-2"><a class="toc-link" href="#%F0%9F%94%B9-4-%E8%BE%93%E5%87%BA%E7%BB%93%E6%9E%9C%E8%AF%A6%E8%A7%A3"><span class="toc-number">1.4.</span> <span class="toc-text">🔹 4. 输出结果详解</span></a></li><li class="toc-item toc-level-2"><a class="toc-link" href="#%F0%9F%94%B9-5-%E9%82%BB%E6%8E%A5%E5%9B%BE%EF%BC%88Adjacency-Graph%EF%BC%89%E6%9E%84%E5%BB%BA"><span class="toc-number">1.5.</span> <span class="toc-text">🔹 5. 邻接图（Adjacency Graph）构建</span></a></li><li class="toc-item toc-level-2"><a class="toc-link" href="#%F0%9F%94%B9-6-%E5%8F%AF%E8%A7%86%E5%8C%96%E6%8A%80%E5%B7%A7"><span class="toc-number">1.6.</span> <span class="toc-text">🔹 6. 可视化技巧</span></a></li><li class="toc-item toc-level-2"><a class="toc-link" href="#%F0%9F%94%B9-7-%E5%85%B8%E5%9E%8B%E5%BA%94%E7%94%A8%E5%9C%BA%E6%99%AF"><span class="toc-number">1.7.</span> <span class="toc-text">🔹 7. 典型应用场景</span></a></li><li class="toc-item toc-level-2"><a class="toc-link" href="#%F0%9F%94%B9-8-%E7%BC%96%E8%AF%91%E9%85%8D%E7%BD%AE%EF%BC%88CMakeLists-txt%EF%BC%89"><span class="toc-number">1.8.</span> <span class="toc-text">🔹 8. 编译配置（CMakeLists.txt）</span></a></li><li class="toc-item toc-level-2"><a class="toc-link" href="#%F0%9F%94%B9-9-%E5%91%BD%E4%BB%A4%E8%A1%8C%E4%BD%BF%E7%94%A8%E6%96%B9%E5%BC%8F"><span class="toc-number">1.9.</span> <span class="toc-text">🔹 9. 命令行使用方式</span></a></li><li class="toc-item toc-level-2"><a class="toc-link" href="#%E2%9C%85-%E4%B8%89%E3%80%81%E6%80%BB%E7%BB%93"><span class="toc-number">1.10.</span> <span class="toc-text">✅ 三、总结</span></a></li><li class="toc-item toc-level-2"><a class="toc-link" href="#%E4%BB%A3%E7%A0%81%E5%AE%9E%E7%8E%B0"><span class="toc-number">1.11.</span> <span class="toc-text">代码实现</span></a></li></ol></li></ol></div></div><div class="card-widget card-recent-post"><div class="item-headline"><i class="fas fa-history"></i><span>最新文章</span></div><div class="aside-list"><div class="aside-list-item no-cover"><div class="content"><a class="title" href="/2025/10/05/2025-10-05-lio_sam/" 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